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Ian Ruginski
Interdisciplinary researcher with a PhD in psychology and 6+ years of quantitative and qualitative research experience. I leverage theories of emotions, visual processing, and spatial cognition to study navigation and memory in virtual environments & influence the design of data visualizations.
I have coauthored many peer-reviewed scientific articles and taught and developed R learning materials for PhD level social-science statistics classes.
Education
PhD. Psychology, Cognition & Neural Science area
University of Utah
Salt Lake City, UT
2018 - 2013
- Conducted and published research on data visualization design, spatial navigation in real, virtual, and desktop environments, & effects of emotions on perception and navigation.
B.A., Cognitive Science, Religious Studies
Vassar College
Poughkeepsie, NY
2015 - 2009
Research Experience
Postdoctoral Fellow
Geographic Information and Visualization Group
University of Zurich
2020 - 2019
- Developed and analyzed behavioral studies to evaluate digital displays and maps, including using eye-tracking, biometric, and questionnaire data
- Managed multiple projects while advising M.S. and Ph.D students.
Postdoctoral Fellow
Spatial Cognition & Navigation Project
University of Utah
2019 - 2018
- Go-to statistician on multiple projects; researched combined effects of culture and behavior on navigation and spatial memory.
- Data wrangling, analysis, and visualization for database across 6 international fieldsites in the U.S., Africa, and South America.
Data Science Fellow
Sorenson Impact Center
Salt Lake City, UT
2018 - 2017
- Worked on public and private sector projects implementing impact measurement.
- Provided customized data diagnostics, visualizations, and reports for clients.
- Learned and implemented best practices around data security and version control.
Teaching Experience
Graduate Teaching Assistant
University of Utah
Salt Lake City, UT
2018 - 2013
- TA & lecturer for Graduate Quantitative Methods I & II, Structural Equation Modeling.
- Taught graduate students data processing, analysis, and interpretation pipeline in R.
- Topics included multilevel models, causal inference, measurement, generalized linear modeling, & time-based models.
Department Statistical Consultant
University of Utah
Salt Lake City, UT
2018 - 2017
- Consulted for statistical & code problems on a case by case basis.